Instructions to use reeddg/ll7class with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use reeddg/ll7class with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="reeddg/ll7class")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("reeddg/ll7class") model = AutoModelForSequenceClassification.from_pretrained("reeddg/ll7class", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 985f2e685cee31de2d1f48f999cec8b9f1f2d78afb023a269ee10e228b6b83e6
- Size of remote file:
- 9.89 GB
- SHA256:
- c279d6783fc40855c9d4b4123c638f8a3a0e2c869e45d7e85f4043f036591204
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